code: def fit(self, X, column):
      self._old_column = column
      self._uniq_values = np.unique(X[column].values)
      # self._uniq_values = [str(u) for u in self._uniq_values]
  
      if len(self._uniq_values) == 2:
          self._new_columns.append(
              column + "_" + str(self._uniq_values[1])
          )
      else:
          for v in self._uniq_values:
              self._new_columns.append(column + "_" + str(v))
  
file_path: mljar-supervised/supervised/preprocessing/label_binarizer.py
imports: import json
  import numpy
label_desc: Use image node_id 2 for calling the LabelBinarizer obj's underlying member method code with example usage: obj.fit(X, column) without return types